Machine learning with decentralized training data using federated learning on Amazon SageMaker | Amazon Web Services
In this post, we discuss how to implement federated learning on Amazon SageMaker to run ML with decentralized training data.
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Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift | Amazon Web Services
Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every day. Many practitioners are extending these…
Intelligent video and audio Q&A with multilingual support using LLMs on Amazon SageMaker | Amazon Web Services
Digital assets are vital visual representations of products, services, culture, and brand identity for businesses in an increasingly digital world. Digital assets, together with recorded user behavior, can facilitate customer…
Zero-shot and few-shot prompting for the BloomZ 176B foundation model with the simplified Amazon SageMaker JumpStart SDK | Amazon Web Services
Amazon SageMaker JumpStart is a machine learning (ML) hub offering algorithms, models, and ML solutions. With SageMaker JumpStart, ML practitioners can choose from a growing list of best performing and…
Build production-ready generative AI applications for enterprise search using Haystack pipelines and Amazon SageMaker JumpStart with LLMs | Amazon Web Services
This blog post is co-written with Tuana Çelik from deepset. Enterprise search is a critical component of organizational efficiency through document digitization and knowledge management. Enterprise search covers storing documents…
Build a centralized monitoring and reporting solution for Amazon SageMaker using Amazon CloudWatch | Amazon Web Services
Amazon SageMaker is a fully managed machine learning (ML) platform that offers a comprehensive set of services that serve end-to-end ML workloads. As recommended by AWS as a best practice,…
Host the Spark UI on Amazon SageMaker Studio | Amazon Web Services
Amazon SageMaker offers several ways to run distributed data processing jobs with Apache Spark, a popular distributed computing framework for big data processing. You can run Spark applications interactively from…
Use the Amazon SageMaker and Salesforce Data Cloud integration to power your Salesforce apps with AI/ML | Amazon Web Services
This post is co-authored by Daryl Martis, Director of Product, Salesforce Einstein AI. This is the second post in a series discussing the integration of Salesforce Data Cloud and Amazon…
Scale training and inference of thousands of ML models with Amazon SageMaker | Amazon Web Services
As machine learning (ML) becomes increasingly prevalent in a wide range of industries, organizations are finding the need to train and serve large numbers of ML models to meet the…